Changes in vibration mechanics may provide information concerning abnormalities and failures related to rotating equipment. Conventional methods for analyzing changes in vibrational data related to rotating equipment can be based on the first principle calculations and physics-based models. Even though conventional solutions may allow detecting failures in the rotating equipment as they occur, they sometimes fail to provide sufficiently early warnings for the failures.
One feature that may provide an early indication of a failure in rotating equipment is a slow roll vector. Conventional methods for capturing the slow roll vector sometimes use higher sampling rate data that may not be available.